斯瓦拉姆: Osprey优化算法为基础的节能集群头选择无线传感器网络为基础的物联网
Ramasubbareddy Somula1, Yongyun Cho1, Bhabendu Kumar Mohanta2
1Department of Information and Communication Engineering, Sunchon National University, Suncheon-si 57922, Republic of Korea.
Sensors (Basel, Switzerland)
|January 23, 2024
概括
SWARAM算法通过优化无线传感器网络中的集群头选择来增强物联网 (IoT) 网络,提高能源效率和网络寿命. 这种方法可以将数据包交付和网络寿命提高10%.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 网络工程 网络工程
背景情况:
- 物联网 (IoT) 网络依赖于传感器节点来收集各种应用中的数据,例如精密农业.
- 有限的电池寿命和能源消耗是物联网的关键挑战,影响网络寿命和维护.
- 集群对于物联网能源效率至关重要,但不适当的集群头 (CH) 选择会导致能源漏洞和性能下降.
研究的目的:
- 通过提出一个节能集群头 (CH) 选择算法来解决物联网无线传感器网络中的能量漏洞问题.
- 通过优化CH选择,减少冗余数据传输和节约能源来提高网络寿命和性能.
- 为智能CH选择引入基于 Osprey优化算法的SWARAM (传感器网络带有Osprey启发的路由算法).
主要方法:
- SWARAM方法涉及两个阶段:使用欧几里德距离的集群形成和通过SWARAM技术的CH选择.
- 拟议的算法是使用MATLAB 2019a.a进行模拟和评估的.
- 性能与现有的算法进行了比较:EECHS-ARO,HSWO和EECHIGWO.
主要成果:
- 与现有方法相比,SWARAM算法在数据包交付比率上得到了10%的改进.
- 通过有效的节能和CH选择策略,网络寿命延长了10%.
- 由于优化集群和能源管理,整体网络性能显著改善.
结论:
- 通过选择最佳集群头,SWARAM算法有效地解决了物联网网络中的能量漏洞问题.
- 在物联网应用中,SWARAM为提高能源效率,网络寿命和整体性能提供了一个有前途的解决方案.
- 拟议的方法为物联网环境的无线传感器网络集群提供了实质性的进展.
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